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Mazen Elsafty

Mazen Elsafty

Data Scientist

EELU | egypt

Technologies

My Portfolio Highlights

My New Github

Medical Representative

My New Github

Charity Donor Predictor

My New Github

Medical Representative

Mazen Elsafty I am a data enthusiast with a Bachelor’s degree in Computer Science, specializing in Information Technology. My academic background has provided me with a robust technical foundation, but my journey into the world of data ignited a deeper passion for its transformative potential. I am fascinated by how data can drive innovation, optimize business operations, and influence strategic decision-making on a global scale. To cultivate this passion, I have dedicated myself to mastering data science, data analysis, and machine learning, supported by a strong understanding of statistics, probability, and mathematics. Over the course of my learning, I have developed a data-driven mindset, enabling me to extract valuable insights and translate them into actionable solutions. My experience includes working on diverse projects, completing internships with reputable companies, and applying my knowledge to real-world challenges. These opportunities have honed my technical expertise and deepened my understanding of the practical applications of data in solving complex problems. I am committed to leveraging data to create meaningful impact, continuously expanding my skills, and contributing to innovative solutions that drive progress in businesses and beyond.

My Work

Take a look at my latest work.

github

Medical Representative

github

Charity Donor Predictor

github

Ames House Price Prediction

PythonTheory
github

California House Price Prediction

PythonTheory
github

SMS Spam Classifier using Naive Bayes

PythonTheory
github

Movies Analysis

Python
github

Medical Representative

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Introduction to Python
Intermediate Python
Data Manipulation with pandas
Manipulating Time Series Data in Python

My Work Experience

Where I've interned and worked during my career.

Digital Egypt Pioneers Initiative - DEPI | Apr 2024 - Dec 2024

IBM Data Science

of Communications and Information Technology, aims to cultivate a skilled workforce in digital technology and data science through advanced training programs and certifications. 219 hours My Engagement in DEPI: IBM Data Science Grant Program: Completed an extensive grant-supported program by IBM under DEPI, focusing on mastering tools and techniques for data analysis, machine learning, data visualization, data cleaning, EDA, statistics, web scraping, Python programming, and SQL. Hands-on Tools and Libraries: Gained proficiency in Anaconda and Jupyter Notebook. Worked extensively with libraries like Pandas, NumPy, Scikit-learn, Beautiful Soup, Requests, and SQL Magic. Applied machine learning techniques, including supervised and unsupervised models, cross-validation, grid search, and model tuning. Real-World Project Experience: Ames House Price Prediction: Built predictive models to estimate house prices based on key features. Finding Donors Predictor: Developed models to identify potential donors for charity organizations. Chicago Web Scraping Project: Scraped real estate data from Chicago listings and created a structured dataset. Medical Representative Analysis: Analyzed performance metrics and trends for medical representatives. SMS Spam Classifier: Created a machine learning model to classify SMS messages as spam or legitimate. Technologies and Techniques: Utilized advanced data preprocessing, feature engineering, and machine learning pipelines to streamline workflows. Worked on model evaluation and tuning to optimize performance. Professional Development: Received specialized training in freelancing, soft skills, and English proficiency, supporting career growth and communication skills. Through DEPI, I built a strong foundation in data science, applying theoretical concepts to solve real-world challenges. My work reflects a commitment to leveraging data-driven insights.
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Bharat Intern | Aug 2024 - Sep 2024

Data Scientist

Bharat Intern is a premier internship platform that bridges the gap between education and industry. It provides students and young professionals with meaningful opportunities in diverse fields such as technology, data science, marketing, and more. My Contributions at Bharat Intern: Titanic Survival Prediction Project: Developed machine learning models, including Logistic Regression, Decision Trees, and Random Forests, to predict passenger survival on the Titanic. Conducted data preprocessing, feature engineering, and model evaluation to improve predictive accuracy. CNN-Based Image Classification Project: Built a Convolutional Neural Network (CNN) to classify images of cats and dogs, gaining hands-on experience with deep learning. Utilized frameworks such as TensorFlow and Keras, focusing on model architecture, optimization, and validation. Skill Development: Strengthened expertise in data preprocessing, including handling missing values, normalization, and data augmentation for image data. Gained experience in model training, fine-tuning, and leveraging collaborative teamwork to deliver high-quality outcomes. Technologies and Tools: Programming Languages: Python. Libraries: Pandas, NumPy, Matplotlib, Scikit-learn, TensorFlow, and Keras. Machine Learning Techniques: Supervised learning, deep learning, and neural network optimization. Development Environments: Jupyter Notebook and Anaconda. At Bharat Intern, I had the opportunity to work on impactful projects, enhancing my technical expertise and teamwork abilities in a dynamic, learning-oriented environment.

NeuronetiX | Aug 2024 - Sep 2024

Data Analyst

NeuronetiX is an innovative technology company specializing in data analytics and artificial intelligence solutions. The company leverages cutting-edge technology to transform data into actionable insights, driving decision-making across diverse industries. My Contributions at NeuronetiX: Data Analysis and Insights: Performed comprehensive data cleaning, preprocessing, and exploratory analysis to identify patterns and trends in large datasets. Applied statistical techniques to derive actionable insights and informed strategic decision-making. Data Visualization and Reporting: Designed interactive dashboards and reports using Power BI and Excel, enabling stakeholders to explore key metrics effectively. Created compelling visualizations to communicate complex data trends and findings clearly. Technical Expertise: Utilized Python libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization. Automated repetitive data tasks to improve efficiency and accuracy in data workflows. Technologies and Tools: Programming Languages: Python. Libraries: Pandas, NumPy, Matplotlib, and Seaborn. Data Visualization Tools: Power BI and Excel. Techniques: Data cleaning, statistical analysis, and exploratory data visualization. At NeuronetiX, I honed my analytical and technical skills, contributing to data- driven projects that empowered businesses to make informed decisions. This experience deepened my understanding of real-world data challenges and solutions.

CodeAlpha | Aug 2024 - Sep 2024

Data Scientist

CodeAlpha is a leading technology and software development company specializing in innovative solutions in data science, machine learning, and software engineering. My Contributions at CodeAlpha: Machine Learning Models: Developed and implemented a linear regression model to predict housing prices, working on feature engineering, data scaling, and model evaluation to enhance prediction accuracy. A/B Testing Analysis: Analyzed and compared product performance in an A/B testing scenario using Bayesian analysis and Chi-Square tests. Delivered actionable insights that guided the marketing team in optimizing strategies for better customer engagement. Stock Price Prediction: Built and trained a Long Short-Term Memory (LSTM) model to predict Microsoft stock prices. Utilized temporal dependencies in stock market data to improve prediction accuracy. Employed time-series data processing techniques, such as sequence generation, lag features, and rolling statistics. Data Preparation and EDA: Collaborated in data collection and preprocessing, including handling missing values, outlier treatment, and feature selection. Conducted exploratory data analysis (EDA) to identify patterns and trends, ensuring data quality and insight generation. Technologies and Tools: Programming Languages: Python. Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, and Keras. Data Analysis Techniques: Bayesian analysis, Chi-Square tests, time-series analysis, and data preprocessing. Development Environments: Jupyter Notebook and Anaconda. Machine Learning Techniques: Regression models, deep learning (LSTM), cross-validation, and hyperparameter tuning. At CodeAlpha, I worked on diverse projects, leveraging cutting-edge tools and techniques to deliver impactful solutions. This experience significantly enhanced my technical expertise and my ability to contribute effectively to collaborative, data-driven environments.

Certiport - A Pearson VUE Business | Jul 2024 - Sep 2024

IT Specialist - Device Configuration and Management

N/A

My Education

Take a look at my formal education

Bachelor of Science in Information Technology, Information TechnologyThe Egyptian E-Learning University - EELU | 2025

About Me

Mazen Elsafty

I am fascinated by how data can drive innovation, optimize business operations, and influence strategic decision-making on a global scale. To cultivate this passion, I have dedicated myself to mastering data science, data analysis, and ML.

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